Novel nomograms based on microvascular invasion grade for early-stage hepatocellular carcinoma after curative hepatectomy

Microvascular invasion (MVI) is a critical risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). This study aimed to firstly develop and validate nomograms based on MVI grade for predicting recurrence, especially early recurrence, and overall survival in patients with early-stage HCC after curative resection. We retrospectively reviewed the data of patients with early-stage HCC who underwent curative hepatectomy in the First Affiliated Hospital of Fujian Medical University (FHFU) and Mengchao Hepatobiliary Hospital of Fujian Medical University (MHH). Kaplan–Meier curves and Cox proportional hazards regression models were used to analyse disease-free survival (DFS) and overall survival (OS). Nomogram models were constructed on the datasets from the 70% samples of and FHFU, which were validated using bootstrap resampling with 30% samples as internal validation and data of patients from MHH as external validation. A total of 703 patients with early-stage HCC were included to create a nomogram for predicting recurrence or metastasis (DFS nomogram) and a nomogram for predicting survival (OS nomogram). The concordance indexes and calibration curves in the training and validation cohorts showed optimal agreement between the predicted and observed DFS and OS rates. The predictive accuracy was significantly better than that of the classic HCC staging systems.


Patients and study design
The database was retrospectively derived from patients with HCC who underwent hepatectomy at the First Affiliated Hospital of Fujian Medical University (FHFU) and the Mengchao Hepatobiliary Hospital of Fujian Medical University (MMH) from March 2015 to March 2020.
The inclusion criteria for patients with HCC patients in this study were: (1) early-stage HCC (BCLC stage 0 or A) diagnosis that was confirmed by postoperative pathology; (2) Child-Pugh A or B liver function before surgery; (3) R0 surgical resection of the tumor with curative intent; (4) all patients who survived for at least 30 days after surgery; (5) no preoperative anticancer treatments that could introduce any bias; and (6) clinicopathological data and follow-up information were available.Patients with the following criteria were excluded: (1) recurrent HCC, (2) combined hepatocellular cholangiocarcinoma, (3) previous history of malignancy, and (4) age < 18 years.R0 surgical resection was defined as complete tumor resection with histopathologically tumorfree resection margins.
Nomogram models were constructed on the datasets from the FHFU, which were also validated using bootstrap resampling as internal validation, and the dataset from the MMH was used for external validation.This study was approved by the Ethics Review Committee of the First Affiliated Hospital of Fujian Medical University and the Ethics Review Committee of Mengchao Hepatobiliary Hospital of Fujian Medical University.Written informed consent was obtained from all subjects before the operation.All procedures were performed in accordance with the Declaration of Helsinki.

Clinical variables
Demographic, laboratory, and HCC pathological data were collected.The laboratory tests included various tests for routine blood parameters, full sets of tests for blood clotting, full sets of tests for blood biochemistry, and hepatitis virus markers.Imaging data included, but were not limited to, the number of tumors, presence of satellite nodules, the diameter of the largest nodule, tumor capsule, and cirrhosis based on preoperative contrastenhanced computed tomography (CT) or magnetic resonance imaging (MRI).The diagnosis and grade of MVI were confirmed according to the Standard for Diagnosis and Treatment of Primary Liver Cancer 4 by 2 independent pathologists.In case of any doubt, the final decision was determined after MDT discussion.Briefly, the grade of MVI is defined as follows: M0: no MVI; M1: the number of MVI is < 5 and at a distance of ≤ 1 cm from the tumor; M2: the number of MVI is > 5 or at a distance of > 1 cm from the tumor (Fig. 1) 4 .

Statistical analysis
Continuous variables are expressed as mean ± standard deviation.Chi-squared or Fisher's exact tests were used to assess differences in categorical variables.The Wilcoxon rank-sum test was used to compare continuous variables between groups.In this study, the cut-off values of continuous variables were established using the X-tile software version 3.6.1 (Yale University School of Medicine, New Haven, Connecticut, United States) for widely clinical application.For DFS and OS curves during follow-up, Kaplan-Meier curves, log-rank Mantel-Cox test, and Cox proportional hazards regression analyses were used.Nomograms were generated using the rms package in R software version 3.5.2(R Foundation for Statistical Computing, Vienna, Austria) 9 .The predictive accuracy and discriminative ability of the nomogram were assessed using the concordance index (C-index) and calibration curves.The larger the C-index, the more accurate the prognostic prediction is.A value of P < 0.05 was considered significant.All covariates met the Cox proportional hazard assumption, as determined by the Schoenfeld residuals.Variance inflator factor was used to assess multicollinearity in all estimated models; there was no indication of multicollinearity.

Establishment of nomogram model for postoperative early-relapse/OS and evaluation of its discriminability and calibration
Based on the independent prognostic factors, nomograms for DFS and OS in the study cohort were established (Fig. 3).The results are shown in Supplementary Table 2.The C-index of the nomogram for DFS was 0.775 (95% confidence interval [CI] 0.720-0.830).The C-index for OS was 0.812 (95% CI 0.732-0.892).The validation showed excellent consistency between the observed and predicted 8-month, 1-, 2-and 3-year DFS, and 8-month, 1-, 2-and 3-year OS (Fig. 3); with a C-index of 0.865 (95% CI 0.806-0.924)for DFS and a C-index of 0.839 for OS (95% CI 0.675-1.00) in the internal validation cohort, and with a C-index of 0.857 (95% CI 0.763-0.951)for DFS and a C-index of 0.842 (95% CI 0.708-0.970)for OS in the external validation cohort (Supplementary Table 2).Calibration curves of internal verification and external verification with slopes closed to 1 and all p-value greater than 0.05 in the Hosmer and Lemeshow test, showed good consistency between the observed and predicted events (Fig. 4).Taken together, the nomogram models were able to accurately predict postoperative relapse and OS in patients with BCLC early-stage HCC.

Comparison of predictive accuracy between the nomogram models and the classical staging systems
The predictive value of the constructed model, in terms of clinical practicability, was compared with that of the 8th edition American Joint Committee on Cancer (AJCC) staging system, the BCLC staging system, the Japan Integrated Staging Score (JIS) and the Hong Kong Liver Cancer prognostic classification scheme (HKLC).The results are shown in Supplementary Table 2.In the training cohort, the C-index of the nomogram for DFS and OS was 0.775 and 0.812, respectively, which was significantly higher than the AJCC (DFS: 0.591; OS: 0.588), BCLC (DFS: 0.601; OS: 0.599), JIS (DFS: 0.589; OS: 0.592), and HKLC (DFS: 0.595; OS: 0.612) staging systems.Similarly, in the validation cohort, the C-index of the nomogram for DFS (internal cohort: 0.865; external cohort: 0.857) and OS (internal cohort: 0.839; external cohort: 0.842), was also significantly higher than the AJCC (internal cohort: 0.622, external cohort: 0.586 for DFS; and internal cohort: 0.615, external cohort: 0.578 for OS), BCLC (internal cohort: 0.602, external cohort: 0.574 for DFS; and internal cohort: 0.608, external cohort: 0.571 for OS), JIS (internal cohort: 0.606, external cohort: 0.581 for DFS; and internal cohort: 0.599, external cohort: 0.574 for OS), HKLC (internal cohort: 0.625, external cohort: 0.558 for DFS; and internal cohort: 0.619, external cohort: 0.541 for OS) staging systems.Overall, the nomogram models exhibited superior predictive accuracy to that of these authoritative staging systems for DFS and OS.

Discussion
Although patients with BCLC early-stage HCC typically have a more favorable prognosis compared to those with late-stage HCC characterized by macrovascular invasion and multiple intrahepatic metastases, a significant proportion of patients still experience recurrence and metastasis.The presence of macrovascular invasion is universally recognized as a highly influential factor in predicting poor prognosis among patients with early-stage HCC 4,8,9 .Moreover, recent research has demonstrated a strong correlation between the grade of macrovascular invasion and postoperative recurrence, particularly early recurrence 8,[10][11][12][13] .Neither of the two most commonly used pathological staging systems for hepatocellular carcinoma (HCC) incorporates the presence of MVI as a criterion.Currently, there is a lack of reported predictive models utilizing the MVI grading system to identify   The histopathological types and grades of MVI serve as indicators of the histopathological transformations that transpire when a cancer embolus within a vessel develops into a satellite lesion or a metastatic site.www.nature.com/scientificreports/Consequently, the histopathological type of MVI can be employed as a morphological marker for assessing the biology and advancement of HCC 4,14,15 .The detectability rate of MVI in patients with early-stage HCC ranges from 12.4% to 33.1%, and the prognostic significance of MVI in this patient population following curative surgery is still a matter of debate [16][17][18] .In our study, we found that MVI was an independent risk factor associated with DFS and OS (Fig. 2, P < 0.001), with a detection rate of 39.1% (275/703).Recently, studies indicated that the tumor microenvironment in MVI-positive HCC patients was more immunosuppressive than that in MVInegative HCC patients.This environment could promote tumor progression by activating signaling pathways that enhance tumor cell proliferation, migration, and angiogenesis including HIF-1 pathway, Wnt pathway, MAPK pathway, and Ras pathway [19][20][21] .Additionally, it recruits inhibitory immune cells and upregulates immune checkpoints to mediate immune escape in tumors [22][23][24] .Ultimately, these mechanisms jointly contribute to recurrence and metastasis in MVI-positive HCC patients after curative hepatectomy.The relationship between tumor size and patient prognosis is widely acknowledged, particularly in cases of HCC.Tumor enlargement has been consistently associated with a poor prognosis in HCC patients, leading to the establishment of cut-off values in various guidelines to predict prognosis.This is due to the non-linear nature of the relationship between tumor size and poor prognosis.For the purpose of this study, the cut-off values of 5 and 10 cm were utilized.Notably, our study revealed that tumors with a diameter exceeding 10 cm were identified as a significant risk factor for recurrence.Interestingly, despite AFP being widely recognized as a conventional clinical marker for diagnosing and prognosticating patients with HCC, our study found that it did not independently correlate with prognosis in early-stage HCC following curative hepatectomy.This observation may be attributed to the limited sensitivity of AFP in predicting the prognosis of early-stage HCC.Previous reports have indicated that AFP remains undetectable in approximately 30-35% of individuals with primary HCC, while elevated AFP levels can also be observed in individuals with normal health 25 .It is noteworthy that AFU emerged as a significantly independent factor associated with OS in early-stage HCC.Existing literature reports AFU as a specific marker for HCC, demonstrating superior sensitivity and specificity compared to AFP in the diagnosis of HCC.Particularly, AFU exhibits high accuracy in distinguishing AFP-negative cases and early-stage HCC.Consequently, the dynamic monitoring of AFU holds immense importance in the diagnosis and prognosis of early-stage HCC 26 .Besides that, ALP is also a valuable predictor of early-stage HCC patients' DFS after curative hepatectomy in our nomogram.ALP is an important indicator of liver function and highly associated with some hepatic diseases including hepatitis, cirrhosis and HCC 27 .It has recently been reported that ALP levels could be used to monitor and predict recurrence and metastasis in HCC patients 28 .Previous studies have found that high level of ALP was related to tumor cell proliferation and epithelial-mesenchymal transition (EMT) 29,30 .Besides, the liver is highly susceptible to oxidative stress-induced damage, with ALP serving as a dependable and sensitive marker for assessing oxidative stress.The detrimental effects of oxidative stress on hepatocytes encompass lipid, protein, and DNA impairment, ultimately leading to liver injury 31 .Consequently, these processes can eventually promote the metastasis and recurrence of HCC.Previous research has indicated a correlation between immune function and nutritional status and the prognosis of patients diagnosed with HCC [32][33][34][35] .Within our nomogram models, we have identified several influential immune and nutritional indices, namely neutrophil, monocyte, MCH, PAB, and urea, which can effectively predict prognosis.Notably, patients with low levels of neutrophils and urea, indicative of inadequate protein intake, exhibit a poorer prognosis.The tumor microenvironment is a crucial factor in the development of tumors.The immune and nutritional status, as components of the tumor microcirculation, undoubtedly impact the prognosis of patients with HCC.A growing body of evidence indicates a significant association between fundamental nutritional status, systemic inflammation, and the long-term prognosis of individuals diagnosed with cancer [36][37][38][39] .The presence of malnutrition and compromised immune function not only impacts the efficacy of treatment in individuals diagnosed with malignant tumors, but also increases the susceptibility of patients with HCC to relapse and metastasis 36 .
In recent times, metabolic disorders, specifically lipid metabolism disorders, have gained prominence as a crucial microenvironment contributing to the development of HCC 40,41 .In this study, LDL and Apo-A1, serving as indicators of hepatic lipid metabolism, emerged as significant prognostic factors for early-stage HCC.It is well-established that alterations in liver lipid metabolism are intricately linked to the onset of liver cancer, and it is plausible that non-alcoholic fatty liver disease may be recognized as a principal etiological factor for primary liver cancer in the future 42 .Furthermore, prior research has demonstrated that lipid metabolism disorders can facilitate the proliferation of tumor cells by impeding the apoptosis of hepatocellular carcinoma cells, consequently leading to an unfavorable prognosis 43 .
However, there remains scope for additional enhancements.Initially, our model predominantly relies on datasets obtained retrospectively from two Chinese institutions.Despite the satisfactory performance of the models, certain indices were not consistently gathered in certain countries, such as South Africa.The inclusion of additional cohorts from other institutions across regions may improve the predictive accuracy and universality of models.Furthermore, our models would benefit from external validation using a completely unseen and more diversity dataset, for a more accurate description of models performance.Second, though the sample size in this study is adequate, a larger sample size in conjunction with meaningful information including postoperative adjuvant treatment collected in the future may improve the accuracy of our results.Third, although, HBV infection could strongly influence on prognosis in HCC patients, the HBV-related HCC accounted for most of HCC patients in our country, which leaded it limited influence in our models.Cohort with different eitologies, multi-population and across regions will be included in the future to determine the influence of HBV infection on the prognosis in early-stage HCC patients after curative resection.
In summary, we developed and validated nomograms for predicting recurrence, especially early recurrence, and OS in patients with early-stage HCC after curative surgery.The predictive performances were superior to the common typical HCC staging systems, and they can establish patients with a high risk of recurrence or poor

Figure 1 .
Figure 1.The grade of MVI Standard for Diagnosis and Treatment of Primary Liver Cancer.(a) M0: no MVI; (b) M1: the number of MVI is < 5 and at a distance of ≤ 1 cm from the tumor; (c) M2: the number of MVI is > 5 or at a distance of > 1 cm from the tumor.

Figure 2 .
Figure 2. Kaplan-Meier estimates of the prognosis of patients with early-stage HCC according to MVI grade.(a) The MVI grade satisfactorily determined the disease-free survival (DFS) in the whole cohort; (b) The MVI grade satisfactorily determined the overall survival (OS) in the whole cohort.
patients with early-stage HCC who are at a high risk of recurrence or have a poor prognosis.The development of such a model would be advantageous in order to establish a system for early and continuous monitoring or prompt postoperative adjuvant therapy for HCC patients.Consequently, nomograms were developed utilizing the MVI grading system to predict recurrence and overall survival in early-stage HCC patients who underwent curative surgery.Subsequent validation demonstrated a favorable concordance between the nomogram predictions and observed outcomes in terms of predictive probability.Furthermore, our nomograms exhibited superior predictive efficacy compared to the conventional BCLC and AJCC staging systems.The prognosis of patients with HCC is mainly affected by: (1) patient factors, such as immune function, nutritional state, liver function, and status of hepatitis virus infection; (2) tumor factors, such as tumor diameter, MVI classification, and satellite nodules; and (3) factors of treatment, in particularly adjuvant treatment after surgery.In our study, nine of the twelve risk factors associated with recurrence or OS were patient factors, including neutrophil, monocyte, ALP, PAB, MCH, Urea, LDL, Apo-A1, and TT levels, while three factors were tumor-related factors including tumor size, MVI classification, and AFU.These results indicate that the prognosis of HCC is a multifactorial and complex process.